High operating temperatures can severely affect the performance, power consumption and reliability of a circuit system. With the continued scaling of integrated circuit technologies, high power density and the resulting difficulties in managing temperatures have become a major challenge facing designers at all design levels. Computer modeling tools have been employed to predict and simulate the thermal behavior of both physical and virtual structures.
A printed circuit board is typically a layered composite consisting of copper foil and a glass-reinforced polymer (FR-4). It mechanically supports and electrically connects electronic components or electrical components. Printed circuit boards are used in all but the simplest electronic products. They are also used in some electrical products, such as passive switch boxes. A common type of printed circuit board is usually 10 cm wide, 15 cm long and a few millimeters thick. Printed circuit boards can be singled sided, double sided and multilayered. Multilayer printed circuit boards have one or multiple conductor patterns (layers) inside the board, insolated by dielectric layers. This increases the area available for wiring. A smart phone may have a printed circuit board consisting of more than ten layers. Through the conductor layers, a printed circuit board can help to remove component heat. To preserve component reliability, efficient thermal design and management is needed.
When performing a steady-state thermal analysis on a printed circuit board, one of the critical parameters is the effective thermal conductivity. The accuracy of the effective thermal conductivity value for each of the printed circuit board layers can determine the accuracy of the thermal model. No two printed circuit boards are designed alike, but employing an accurate three-dimensional model to predict temperature distribution takes an excessive amount of time. A current method takes a digital image of each layer and converts it into a black and white image. Black is assigned to conductor and white assigned to dielectric. The image is then divided into patches based on inputs from the user. These patches are then converted into effective thermal conductivities by analyzing each row and column. This process often leads to under-prediction of effective thermal conductivities and the use of a correction factor to make up for this error.